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CFP: ML4Audio @ NIPS 2017

Audio signal processing is currently undergoing a paradigm change, where data-driven machine learning is replacing hand-crafted feature design. This has led some to ask whether audio signal processing is still useful in the “era of machine learning.” There are many challenges, new and old, including the interpretation of learned models in high dimensional spaces, problems associated with data-poor domains, adversarial examples, high computational requirements, and research driven by companies using large in-house datasets that is ultimately not reproducible.

ML4Audio will accept five kinds of submissions:
1. novel unpublished work, including work-in-progress;
2. recent work that has been already published or is in review (please clearly refer to the primary publication);
3. review-style papers;
4. position papers;
5. system demonstrations.

Submission format: Extended abstracts as pdf in NIPS paper format, 2-4 pages, excluding references. Submissions do not need to be anonymised. Submissions might be either accepted as talks or as posters. If accepted, final papers must be uploaded on arxiv.org.

(Note that the main conference is sold out already. Presenters of accepted workshop papers will still be able to register for the workshops.)

This workshop especially targets researchers, developers and musicians in academia and industry in the area of MIR, audio processing, speech processing, musical HCI, musicology, music technology, music entertainment, and composition.